Show that if $\{X_n\}$ is a Markov Chain 
Show that, if $\{X_n\}$ is a Markov Chain then
  $$P(X_n=j\mid X_k=l,X_m=i)=P(X_n=j\mid X_m=i),0\leq k<m<n$$

What I did is
$$P(X_n=j\mid X_k=l,X_m=i)=\frac{P(X_n=j,X_k=l,X_m=i)}{P(X_k=l,X_m=i)}=\frac{\sum_{i_{n-1},\dots,i_0}P(X_n=j,X_{n-1}=i_{n-1},\dots,X_{m+1}=i_{m+1},X_m=i,\dots,X_k=l,\dots,X_0=i_0)}{P(X_k=l,X_m=i)}$$
$$=\frac{\sum_{i_{n-1},\dots,i_0}P(X_n=j,X_{n-1}=i_{n-1}, \dots,X_{m+1}=i_{m+1}\mid X_m=i,\dots,X_k=l,\dots,X_0=i_0)P(X_m=i,\dots,X_k=l,\dots,X_0=i_0)}{P(X_k=l,X_m=i)}$$
$$=P(X_n=j\mid X_m=i)*\frac{\sum_{i_{n-1}, \dots,i_0}P(X_m=i,\dots,X_k=l,\dots,X_0=i_0)}{P(X_k=l,X_m=i)}=P(X_n=j\mid X_m=i)$$
Is it right? Is there an easier way?

Yes. That's it.
A Markov chain is a sequence of random variables $\{X_k\}_{k\in\{0..n\}}$ representing $n+1$ subsequent states of a system, such that for all supported values $\{i_k\}_{k\in\{0..b\}}$, and $i_c$, where $0\leq a< b< c\leq n$ we have:
$$\mathsf P(X_c=i_c\mid \bigcap_{k\in\{0..b\}} X_k=i_k)= \mathsf P(X_c=i_c\mid X_b=i_b)$$
So if we let: $K =\{0..a-1\}\cup\{a+1..b-1\}$, then:
$$
\begin{align}
& \mathsf P(X_c=i_c\mid X_b=i_b, X_a=i_a) 
\\[2ex] = & \sum_{\{i_k\}_{k\in K}} {\mathsf P(X_c=i_c\mid X_b=i_b, X_a=i_a,\bigcap_{k\in K}X_k=i_k)\;\mathsf P(\bigcap_{k\in K}X_k=i_k)} 
\\[2ex] = & \mathsf P(X_c=i_c\mid X_b=i_b)\sum_{\{i_k\}_{k\in K}} \mathsf P(\bigcap_{k\in K}X_k=i_k)
\\[2ex] = & \mathsf P(X_c=i_c\mid X_b=i_b)
\end{align}
$$
Which is what you said; but perhaps a little more compactly.
